Dynamic QoS Policy Adjustment for Application Traffic Flows
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Solution Overview
Problem
Existing QoS control policies are inflexible and often determined based on a single traffic type or flow, leading to potential deterioration in application performance as complexity increases, failing to adapt to varying traffic conditions and user experiences.
Innovation Solution
A method and device that dynamically determine the main type of traffic in applications, adjust QoS policies based on performance information, and update these policies to optimize priority across multiple flows, ensuring improved service quality by considering traffic amount, frequency, and priority.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If QoS control policies are determined based on a single traffic type or flow, then the control mechanism remains simple, but application performance deteriorates as complexity increases
Solution Approach 1:
The patent segments the QoS control mechanism by introducing flow-specific QoS parameters and multi-dimensional traffic classification. Instead of applying a single QoS policy to all traffic, the system divides traffic into multiple flows based on application type, traffic pattern, and communication state, applying differentiated QoS control to each segment. This resolves the contradiction by increasing control granularity without overwhelming system complexity.
Solution Approach 2:
The patent implements dynamic QoS policy adjustment by continuously monitoring traffic characteristics and communication states. The QoS parameters are not static but adapt in real-time based on detected traffic patterns, application behavior, and network conditions. This dynamic approach maintains reliable application performance while keeping the control mechanism manageable through event-driven updates rather than continuous complex processing.
2Device complexity
If QoS policies are applied uniformly to all applications, then the control system remains simple, but user experience deteriorates as application complexity increases
Solution Approach 1:
The patent applies local quality by tailoring QoS parameters to specific application requirements and traffic characteristics. Different applications receive customized QoS treatment based on their unique needs - for example, real-time communication applications receive higher priority handling compared to bulk data transfers. This localized approach enhances user experience for each application type while maintaining overall system simplicity through rule-based differentiation.
Solution Approach 2:
The patent utilizes parameter changes by adjusting QoS parameters such as priority levels, bandwidth allocation, and latency thresholds based on application type and communication state. The system dynamically modifies these parameters in response to detected traffic patterns and application behavior, enabling flexible optimization of user experience without requiring complex reconfiguration of the entire QoS control system.
3Adaptability or versatility
If QoS control is based on single traffic type, then policy determination is simple, but adaptability to varying traffic conditions deteriorates
Solution Approach 1:
The patent implements universality by creating a multi-functional QoS control framework that handles diverse application types and traffic patterns through a unified mechanism. The system uses a standardized set of QoS parameters and control procedures that can be applied across different applications and traffic types, enabling the policy determination process to adapt to varying conditions without requiring application-specific complex logic for each case.
Solution Approach 2:
The patent incorporates feedback mechanisms by continuously monitoring traffic characteristics, application performance, and communication states, then using this information to dynamically adjust QoS policies. The feedback loop enables the system to adapt to varying traffic conditions in real-time, with policy determination based on actual observed behavior rather than static pre-configured rules, maintaining simplicity through reactive rather than proactive complex decision-making.
Data Source
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AI summary
A method of controlling Quality of Service (QoS) of an application includes: determining a main type of traffic of the application; determining a QoS control policy to be applied to each of a plurality of flows generated by execution of the application according to the determined main type of traffic; obtaining performance information about traffic of the application using traffic transmitted and received through the plurality of flows; and changing a QoS control policy to be applied to at least one of the plurality of flows, based on the obtained performance information about the traffic.